An Epic Blog Post: How to Improve Patient Matching in Epic® Identity™
Epic® EHRs hold records for 54% of patients in the US, a number that grows every day. And Epic has evolved to become a one-stop shop for an organization’s software needs – including infrastructure for communication and collaboration across the healthcare organization – which is why organizations are willing to shell out $700 million or more to implement an Epic solution.
But while Epic is a fantastic EHR system, it has one foundational component that is far from fantastic: Epic® Identity™, it’s master patient index (MPI) component.
Epic Identity manages patient records, including identifying and remediating duplicate patient records within the organization. While many HIM Directors hoped that Epic Identity might solve their patient matching headaches, they’re facing a familiar problem – long task lists of flagged “potential matches” needing review and remediation, and upwards of 20% duplicate rates in their MPIs.
This drastically diminishes the value of their huge Epic investment, because all of these duplicates lead to decreased quality of care, decreased patient safety and privacy, lost revenue from claims inefficiencies, redundant tests and procedures, and increased IT and labor expenditures – including hiring teams of data stewards to manually review and remediate “potential matches.”
Epic Identity, like most conventional MPIs, struggles to resolve duplicates when the demographic data between two records does not perfectly match – for example, due to typos and misspellings, out-of-date values, and missing data elements. Epic Identity will then flag these “potential matches” for manual review and remediation by a data steward.
This is where Verato comes in.
Verato offers a system-agnostic and SaaS-based solution called Verato Auto-Steward™ that lets organizations keep using Epic Identity as their MPI – but simply makes Epic Identity work better.
Verato Auto-Steward is a cloud-based solution that seamlessly connects with Epic and resolves “potential matches” before they enter the data stewardship queue. It simply makes the patient matching component of Epic Identity work better, without disrupting any of the other core MPI functionality.